code: def testNoGradients(self):
      for i, dtype in enumerate(
          [dtypes.half, dtypes.float32, dtypes.float64]
      ):
          # Note that we name the variables uniquely here since the variables don't
          # seem to be getting deleted at the end of the loop.
          var0 = resource_variable_ops.ResourceVariable(
              [1.0, 2.0], dtype=dtype, name="a%d" % i
          )
          var1 = resource_variable_ops.ResourceVariable(
              [3.0, 4.0], dtype=dtype, name="b%d" % i
          )
  
          # pylint: disable=cell-var-from-loop
          def loss():
              return 5 * var0
  
          # pylint: enable=cell-var-from-loop
          sgd_op = gradient_descent.GradientDescentOptimizer(3.0)
          with self.assertRaisesRegex(ValueError, "No gradients"):
              # var1 has no gradient
              sgd_op.minimize(loss, var_list=[var1])
  
imports: from tensorflow.python.distribute import cross_device_ops
  from tensorflow.python.distribute import distribute_utils
  from tensorflow.python.distribute import mirrored_strategy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import clip_ops
  from tensorflow.python.ops import gradients_util
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import state_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.training import adam
  from tensorflow.python.training import gradient_descent
label_desc: Use image node_id 5 for calling the OptimizerTest obj's underlying member method code with example usage: obj.testNoGradients() and returns: unknown